EP0927348B1 - Procede et dispositif pour controler automatiquement par voie optique la qualite de produits plats et lisses - Google Patents
Procede et dispositif pour controler automatiquement par voie optique la qualite de produits plats et lisses Download PDFInfo
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- EP0927348B1 EP0927348B1 EP97909252A EP97909252A EP0927348B1 EP 0927348 B1 EP0927348 B1 EP 0927348B1 EP 97909252 A EP97909252 A EP 97909252A EP 97909252 A EP97909252 A EP 97909252A EP 0927348 B1 EP0927348 B1 EP 0927348B1
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Images
Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B28—WORKING CEMENT, CLAY, OR STONE
- B28B—SHAPING CLAY OR OTHER CERAMIC COMPOSITIONS; SHAPING SLAG; SHAPING MIXTURES CONTAINING CEMENTITIOUS MATERIAL, e.g. PLASTER
- B28B17/00—Details of, or accessories for, apparatus for shaping the material; Auxiliary measures taken in connection with such shaping
- B28B17/0063—Control arrangements
- B28B17/0072—Product control or inspection
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
- G01J3/46—Measurement of colour; Colour measuring devices, e.g. colorimeters
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/89—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles
- G01N21/892—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles characterised by the flaw, defect or object feature examined
- G01N21/898—Irregularities in textured or patterned surfaces, e.g. textiles, wood
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- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
- G06T7/001—Industrial image inspection using an image reference approach
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- G06V10/56—Extraction of image or video features relating to colour
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Definitions
- the invention relates to a method for automatic optical quality control of flat, flat products with colored and reflecting or partially reflecting surface, especially tiles, as in the preamble of Claim 1 is specified.
- the candidate is also included a color camera.
- the color vector of each pixel the image obtained from the test object forms an address for the table classifier and reads the one below it Address saved color class code. With that lies behind processing of the entire color image of the test object new image, at which each pixel no longer appears Color vector, but belonging to one of several learned color classes is assigned, i.e. a so-called Color class image.
- PCT publication WO 94/23276 describes how Color deviations by comparing the multidimensional Color vector histograms of a reference and a test object can be measured very precisely with the help of color cameras, without binarizing these histograms.
- PCT publication WO 94/23276 describes how Color deviations by comparing the multidimensional Color vector histograms of a reference and a test object can be measured very precisely with the help of color cameras, without binarizing these histograms.
- various methods of education such comparisons are described.
- WO 93/25894 describes a test station with a Lighting device, several electronic cameras and an evaluation device is known in which for radiometric, geometric and colorimetric calibration of the Image sensors of the cameras in their field of view Brightness, line and structure or color patterns arranged and the image signals thus obtained for extraction calibration data.
- the object of the invention is to create an industrial applicable method with which ceramic tiles and similar products automatically with the same differentiation as sorted into color shade classes by human inspectors and checked for surface defects at the same time can.
- Fig. 1 shows schematically the detection of color shades Tiles.
- a color classifier becomes learned which is the color distribution of a reference surface reproduces. For this the image of the surface of a Reference tile 10 from a color camera 11 under one of Light sources 12 generated suitable diffuse lighting added.
- the color camera 11 can be a matrix camera, which is an areal image of the surface of the reference tile or a part of this surface, or it can be a line scan camera line by line picks up while the reference tile 10 in the arrow direction is passed in front of the color camera 11.
- the of the signals of the individual color components supplied to the color camera 11, in the example shown, the RGB signals are digitized pixel by pixel in analog-digital converters 13.
- the digitized RGB signals of each pixel form an address A0, A1, ... An, which the by Address table memory 14 formed color classifier.
- a table 15 is stored in this table memory by a computing unit 14 during the training phase the histogram of the Color vectors of the color image obtained from the reference tile 10 formed, if necessary generalized and then binarized. This procedure is detailed in documents DE 36 39 636 C2 and WO 94/23276.
- the method described so far can be used in any of the the aforementioned publications performed known manner become. So it is particularly possible to use the reference tile and the test specimens in the known from DE 36 39 636 C2 Way instead of using a color camera with multiple color cameras record the parallel adjacent areas take up. Furthermore, the color classifier can be used instead of in the RGB color space also created in another suitable color space , for example in the IHS color space, in which those of the Color camera supplied RGB signals are implemented as is also known from DE 36 39 636 C2.
- Fig. 2 shows a section through the in the color classifier 14 formed cloud 16 for a constant value of the blue component B.
- the learned reference sequence 16 is in this two-dimensional representation as an area recognize that parallel to the RG level in the drawing level lies. The focus of this area corresponds to the most common color vector of the reference tile.
- the table memory is used for sorting in color shades 14 after the training phase with other, bowl-shaped the reference cloud occupies 16 arranged areas.
- the illustrated shells 21, 22, 23, 24 are an example outside the reference cloud 16 and at a growing distance created by this.
- Appear in the sectional view of Fig. 2 these shells as four annular regions that surround the cross section of the reference cloud 16. Every bowl corresponds to a color shade, the closer to the reference cloud lying bowls correspond to those color nuances, which differs little from the color of the reference tile differentiate.
- the color shade of the shell lies in FIG. 2 21 still very close to the color shade of the reference tile, while the color shade of the bowl 24 is already a very shows significant deviation from the reference tile.
- shells outside the learned reference cloud 16 lie only for reasons the better comprehensibility of the graphic representation. It is also possible to define which shells are within the reference cloud. This matches with then color nuances, which are characterized by the fact that not all colors present in the reference tile in the test object available. Likewise, shells can be determined the partly inside and partly outside the reference cloud lie.
- the shells 21 to 24 according to FIG. 2 set so that they each have a certain constant Distance from the edge of the reference cloud 16 and a constant Have thickness.
- a determination is mathematically simple to be carried out by the computing unit 15 of FIG. 1.
- she has but the disadvantage that it does not take into account that the visual color difference impression rarely coincides with the geometric Distance of the considered color vectors corresponds.
- the geometric distance is two RGB color vectors hardly with the visual color difference impression correlated; the colorimetric corresponds to the RGB color space not the visual color difference impression of humans.
- each one is preferably a shade assigned shells in the three-dimensional color classifier designed to match the visually perceived color nuance correspond.
- the Shells deformed so that they are along the intensity axis are further apart than in the other spatial directions of the color space. This takes into account that many Color nuances mainly from a change in brightness consist of an incorrect dosage of the pigments is caused. They don't originate so much in Color defects in the pigments used, which are usually offered with high accuracy by the pigment industry be, but in the inaccuracy of the concentration of the Pigments.
- Color vectors with a very large deviation from the reference correspond to such large color deviations that no more of a color shade, but of a local color error must be spoken.
- Such local color errors come along tile production often before, for example by infestation with black soot particles, through oil stains etc. you can with the described method simultaneously with the Examination of the color shades can be detected.
- 3 is the area 29, all the positions of the table classifier outside the shades of color included with the code "local color error" documented.
- a commonly used method of detection of surface defects is based on the consideration of the Surface in the bright field.
- This known method is in the Figures 4 and 5 schematically using the example of testing the Surface of a test specimen 30 is shown.
- the surface 31 of the test specimen 30 is combined with a light source 32 illuminated flat angle a.
- a camera 33 preferably is a line scan camera, receives this in the reflection angle a reflected light. If the surface is smooth and is error-free, it reflects the entire light intensity into the pupil of the camera 33.
- the surface 31 has a defect in the form of a depression 34, as in Fig. 5 is shown, part of this recess the reflected light intensity scattered into the room, so that less light enters the entrance pupil of the camera 33 reached. Such errors therefore appear as dark areas in the camera image.
- Fig. 6 shows a tile 40 to be tested, which is in the direction of the arrow is moved and its specular or partially specular Surface 41 from a camera 42 in one relatively flat angle a is observed.
- the camera 42 can be a matrix camera or a line camera, and it can a black and white camera or a color camera.
- a Illumination device 43 has a white luminous surface 44, on which a series of black stripes 45 are attached are aligned parallel to the surface 41 of the tile 40 are.
- the lighting device 43 from a light box 47, the inside contains a plurality of light sources 48 and through the front thereof a translucent plate or film 44 also applied opaque black stripes 45 covered between which the plate or film is 44 bright stripes 46 forms.
- the alternating black and light stripes 45 and 46 thus form the elements of an illumination pattern, that illuminates the surface 41 of the tile 40.
- the line camera 42 sees a line of the mirror image of the Illumination pattern resulting from the advance of the tile 40 successive lines of the image of the tile surface 41 is superimposed. If the reflection on a flawless The tile surface 41 takes place, as in FIG. 6 the position 49 is indicated, this line comes, depending on the thickness of the tile and the angular arrangement of the line scan camera 42 and the lighting device 43, either from a black stripe 45 or between them bright stripes 46 of the luminous surface 44. In any case creates a smooth tile surface when the tile is 40 in the direction of the arrow passes the line camera 40 Image with a homogeneous uniform brightness, that is either equally bright or evenly dark.
- the surface 41 of the tile 40 has an error on, like the dent-shaped error shown in FIG. 6 50, so that between the camera 42 and the lighting device 43 running optical beam through that of 0 ° deviating local inclination of the surface at the reflection point 51 deflected from the original direction, so that it strikes another area of the lighting pattern, in the example shown in FIG. 6 to one light streaks 46.
- an error on like the dent-shaped error shown in FIG. 6 50
- the surface 41 of the tile 40 has an error on, like the dent-shaped error shown in FIG. 6 50, so that between the camera 42 and the lighting device 43 running optical beam through that of 0 ° deviating local inclination of the surface at the reflection point 51 deflected from the original direction, so that it strikes another area of the lighting pattern, in the example shown in FIG. 6 to one light streaks 46.
- the thickness of the tile is 40 is not known, cannot be said from the outset whether the homogeneous image with a flawless surface is constantly bright or constantly dark. But
- camera 42 is a matrix camera, it will not capture only the reflection of a row of the lighting pattern, but the reflection of the entire lighting pattern or a section of it.
- the mirror image taken shows that is, with an error-free surface 41, the alternating ones dark and light stripes 45 and 46 of the lighting pattern. If the surface 41 is defective, it will appear Mirror image again local brightness changes at each location Errors, i.e. light spots in the dark stripes and dark spots in the light streaks.
- a line scan camera to check the entire surface 41 repeats the detection of a line of the illumination pattern must be until the entire surface 41 through the Reflection point of this line has passed, is sufficient when using a matrix camera a single shot in the time at which the captured mirror image of the entire Surface 41 is reflected. If the image field of the Matrix camera or the size of the lighting pattern for this not enough, multiple shots of different ones Areas of the surface 41 of the reflected mirror image be made one after the other.
- the local changes in brightness are primarily by the local changes in the angle of inclination of the reflective Area caused. Even if that happens, that the optical reflected at the bottom of a depression Beam again onto an area of the lighting device 43 strikes, which has the same brightness as the Area on which the reflected on the flawless surface there would be an optical beam a transition zone with between these reflection points other surface inclinations through which the optical beam is so is distracted that he is on the lighting device 43 Scans areas of different brightness. Thereby arise in the image of the camera 42 Surface 41 around the circumference of the depression edge zones different brightness levels that appear clearly to step. Likewise, cracks or ridges cause elongated ones Streaks of different brightness that the Show the course of the surface defect.
- the automatic error detection takes place in the one in FIG. 6 illustrated embodiment by an image computer 52, which the output signal of the camera 42 via a digital-to-analog converter 53 is supplied and for implementation the aforementioned image processing is programmed.
- the Image calculator 52 may include an image memory in which the Image recorded by camera 42 is stored and then is evaluated.
- FIG. 7 shows another embodiment of the arrangement for Detection of surface defects shown.
- the order of FIG. 7 differs from the arrangement of FIG. 6 only by a different design of the lighting device 55 by several parallel to each other and parallel to Surface 41 of the tile 40 arranged elongated filament 56 is formed, which is transverse to the feed direction the tiles extend.
- the remaining parts of the arrangement of Fig. 7 correspond to those of the arrangement of Fig. 6 and are with the same reference numerals as there designated.
- the luminous body 56 for example, by Gas discharge tubes can be formed act as glowing stripes, while the gaps between the Luminous bodies 56 the effect of the dark stripes 45 Illumination device 43 of Fig. 6, so that the Lighting device 55 of FIG.
- FIGS. 8 and 9 show a further embodiment of the Arrangement for the detection of surface defects shown, 8 is a side view and FIG. 9 is an end view shows.
- These figures again show a tile 40 which is in the Arrow direction is advanced and its surface 41 with With the help of a camera 60 and a lighting device 61 in specular reflection is checked for surface defects.
- 8 and 9 are the camera 60 and the lighting device 61 vertically above the tile 40 arranged, and the specular reflection takes place in one Angle of almost 90 °.
- the camera 60 is a line scan camera
- the lighting device 61 consists of a number of punctiform Light sources 62, which are arranged so that error-free Tile surface 41 one from each light source 62 coming light beam that at a point that of the Line camera 60 captured line of tile surface 41 is reflected into the pupil of the line camera 60 entry.
- the arrangement of the light sources 62 of the camera 60 in the reflected on the tile surface 41 Mirror reflection observed, and defects of the tile surface, to deflect the reflected light rays lead, cause in the same way as with the 6 and 7 local brightness changes in the image of the tile surface, which is used to detect the surface defects can be evaluated.
- FIGS. 8 and 9 is favorable when it is for spatial reasons the camera and the To arrange the lighting device so low above the tiles, as required in the arrangements of FIGS. 7 and 8 is.
- This embodiment can also be used instead a line camera, a matrix camera can be used, wherein then instead of the punctiform light sources 62 elongated Luminous elements, for example gas discharge tubes, are used are arranged parallel to the tile surface 41 become.
- the lighting pattern instead of parallel stripes thanks to a two-dimensional arrangement of high contrast Elements (black and white or colored) so that the The light rays are always deflected in both directions to a difference in brightness or a difference in color leads.
- This can be exemplified by a regular Arrangement of black or colored dots on one light background happen.
- the lighting pattern can also depend on that changing surface type to be examined in each case have, which are chosen so that those to be recorded Surface defects maximum changes in brightness or color in the image captured by the camera.
- the structure of the lighting pattern can be changed under computer control. This can be done achieve, for example, that the lighting pattern on a liquid crystal display.
- Tiles for determining color nuances and color errors on the one hand and for the determination of surface defects on the other hand can be done in two different zones become. If the tiles on a conveyor these two can be fed continuously Zones along the conveyor line one behind the other. It However, it is also possible to do the two tests in one common zone to perform simultaneously. In this case preferably the lighting device and the camera for surface testing for a wavelength range designed for those used for color testing Cameras is not sensitive. Such a wavelength range is e.g. the near infrared range from about 700 nm. This measure gives the advantage that the two Systems can be installed in the same zone and don't disturb each other anyway. This allows a more compact and less expensive design in comparison to a system with two separate inspection zones to reach.
- every imaging electronic sensor that an optically recorded image in electrical image signals can implement includes Line and matrix cameras, for example, also point by point working scanners.
- Under a black and white camera is a monochrome imaging sensor of this type to understand the record all gray values between black and white and in Can implement gray scale signals.
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Abstract
Claims (33)
- Procédé de contrôle optique automatique de la qualité de produits plats, lisses avec des surfaces colorées et réfléchissantes ou partiellement réfléchissantes, en particulier des carreaux, lors duquel la surface (41) de chaque produit (40) est détectée optiquement au moins par une caméra électronique (11, 42, 60) et les signaux d'image électriques fournis par la caméra (11, 42, 60) sont exploités pour l'obtention de mesures de qualité selon le procédé du traitement d'image électronique, comprenant les étapes de procédé suivantes:pour l'exécution d'un examen de couleur, on enregistre, sous éclairage diffus de lumière blanche, la surface (41) de chaque produit (41) avec au moins une caméra couleur;par un classement de couleur par élément d'image de l'image de la surface (41) du produit (40) avec un classificateur de couleur (14), qui a été défini comme nuage de référence (16) au moyen de références dites bonnes, acquises précédemment par apprentissage dans l'espace caractéristique défini par les vecteurs de couleur de chaque élément d'image, on produit une image de la surface (41) des produits (40), dans laquelle chaque élément d'image est associé à une nuance de couleur (25, 26, 27, 28);à partir de la distribution de fréquence et/ou de la forme géometrique des nuances de couleur (25, 26, 27, 28) associées aux éléments d'image, on effectue la classification globale du produit (40) dans l'une parmi plusieurs classes prédéterminées de nuances de couleur;pour l'exécution d'un examen de surface, au moins une autre caméra (42; 60) supplémentaire saisit l'image d'un motif d'éclairage d'éléments alternants de luminosité ou de couleur différentes, réfléchie ou partiellement réfléchie sur la surface du produit (41), sous un angle (α) tel que les rayons optiques, passant entre la caméra (42; 60) et le motif d'éclairage, réfléchis sur la surface (41) réfléchissante ou partiellement réfléchissante, soient déviés par des inégalités (50) de la surface, sur des éléments du motif de luminosité ou de couleur différente de celle en cas de surface (41) sans défaut, de sorte que des modifications locales de luminosité et de couleur apparaissent dans l'image prise par la caméra (42, 60);par interprétation des modifications locales de luminosité et de couleur, on identifie les défauts (50) de surface qui en sont la cause;à partir des informations obtenues par les deux examens, on dérive automatiquement des signaux pour le tri des produits (40) par nuances de couleur (25, 26, 27, 28) et par catégories de qualité.
- Procédé selon la revendication 1, caractérisé en ce que des défauts locaux de coloration sont déduits à partir de la distribution de fréquence et/ou de la forme géometrique des nuances de couleurs associées aux éléments d'image (25, 26, 27, 28), lesdits défauts locaux se manifestant par une importante divergence de couleur allant au-delà des nuances de couleurs (25, 26, 27, 28) admissibles.
- Procédé selon la revendication 1 ou 2, caractérisé en ce que pour le tri du produit (40) en nuances de couleur (25, 26, 27, 28) dans l'espace de caractéristique défini par les vecteurs de couleur de chaque élément d'image, des domaines de classification en forme de couches (21, 22, 23, 24) sont placés autour du nuage de référence (16) de la surface de référence acquise par entrainement, lesquels correspondent chacun, avec un écartement géométrique croissant du nuage de référence (16) à une classe de nuance de couleur divergeant d'autant plus de la référence dite bonne.
- Procédé selon la revendication 1 ou 3, caractérisé en ce que les domaines (21, 22, 23, 24) en forme de couches correspondant aux classes de nuances de couleur (25, 26, 27, 28) respectives sont si déplacés et leur forme si déformée, en comparaison avec la position et la forme du nuage (16) de référence, que l'affectation automatique en nuances de couleur (25, 26, 27, 28) correspond autant que possible à celle qui aurait été exécutée par l'examinateur humain, bien que l'espace de couleur du système automatique ne corresponde pas parfaitement à celui de la perception humaine des couleurs.
- Procédé selon la revendication 4, caractérisé en ce que les domaines (21, 22, 23, 24) en forme de couches correspondant aux nuances de couleur respectives (25, 26, 27, 28) ont une forme allongée, alignée dans la direction de l'axe noir-blanc de l'espace de couleur.
- Procédé selon l'une des revendications 3 à 5, caractérisé en ce que les domaines (21, 22, 23, 24) en forme de couches ne se trouvent qu'à l'extérieur du nuage de référence (16).
- Procédé selon l'une des revendications 3 à 5, caractérisé en ce que les domaines (21, 22, 23, 24) en forme de couches ne se trouvent qu'à l'intérieur du nuage de référence (16).
- Procédé selon l'une des revendications 3 à 5, caractérisé en ce que les domaines (21, 22, 23, 24) en forme de couches se trouvent à l'extérieur et à l'intérieur du nuage de référence (16).
- Procédé selon l'une des revendications précédentes, caractérisé en ce que, pour l'établissement de la nuance de couleur globale (25, 26, 27, 28) à partir de l'image des classes de nuance de couleur, on établit l'histogramme des nuances de couleur se trouvant dans l'image des classes des nuances de couleur (25, 26, 27, 28) et en ce qu'on choisit dans l'histogramme une valeur statistiquement significative comme nuance de couleur globale du produit (40).
- Procédé selon la revendication 9, caractérisé en ce que la valeur statistiquement significative est l'abscisse du centre de gravité de l'histogramme des classes de nuance de couleur.
- Procédé selon la revendication 9, caractérisé en ce que la valeur statistiquement significative est l'abscisse du maximum de l'histogramme.
- Procédé selon la revendication 9, caractérisé en ce que la valeur statistiquement significative est l'abscisse de la valeur maximum en pour cent de l'histogramme.
- Procédé selon l'une des revendications 9 à 12, caractérisé en ce que, lors de l'établissement de l'histogramme des classes de nuance de couleur, des fuyards ne sont pas pris en compte dans l'histogramme.
- Procédé selon l'une des revendications 9 à 13, caractérisé en ce que lors de l'établissement de la nuances de couleur globale (25, 26, 27, 28) du produit (40), on tient compte également, en plus des caractéristiques statistiques de l'image des classes de nuance de couleur, de la distribution géométrique de l'image des classes de nuance de couleur existantes déterminées pour chaque élément d'image.
- Procédé selon l'une des revendications 1 à 14, caractérisé en ce que, dans des intervalles de temps déterminés, des références de couleur sont projetées dans le champ d'image de chaque caméra (42, 60) utilisée pour l'examen de couleur et en ce que le système est automatiquement recalibré.
- Procédé selon l'une des revendications 1 à 14, caractérisé en ce que, dans le champ d'image de chaque caméra (42, 60) utilisée pour l'examen de couleur, des références d'image sont superposées en permanence et en ce que le système est automatiquement recalibré à chaque prise de vue.
- Procédé selon la revendication 1, caractérisé en ce que le motif d'éclairage utilisé lors de l'examen de surface est une mire consistant en une alternance de lignes de luminosité différente ou de couleur différente, qui sont disposées parallèlement à la surface du produit (41).
- Procédé selon la revendication 1, caractérisé en ce que la revendication 1, caractérisé en ce que le motif d'éclairage est formé par un arrangement bidimensionnel d'éléments à grand contraste, de luminosité différente ou de couleur différente.
- Procédé selon la revendication 1, caractérisé en ce qu'en fonction du type de surface à analyser, le motif d'éclairage a une structure pour laquelle les défauts de surface (50) à détecter provoquent des modifications maximales de luminosité ou de couleur dans l'image prise par la caméra (11).
- Procédé selon l'une des revendications 1, 17, 18 ou 19, caractérisé en ce que le motif d'éclairage est modifiable par commande par ordinateur.
- Procédé selon la revendication 20, caractérisé en ce que le motif d'éclairage est produit au moyen d'un écran à cristaux liquides.
- Procédé selon la revendication 1 ou l'une des revendications 17 à 21, caractérisé en ce que lors de l'examen de la surface du même endroit de la surface du produit (41) plusieurs images sont prises, respectivement avec d'autres motifs d'éclairage et en ce que les défauts de surface (50) sont déterminés par exploitation de plusieurs images.
- Procédé selon l'une des revendications 1 à 22, caractérisé en ce que l'examen de couleur et l'examen de la surface sont réalisés dans deux zones spatialement séparées.
- Procédé selon l'une des revendications 1 à 22, caractérisé en ce que l'examen de couleur et l'examen de la surface sont réalisés la même zone de l'espace.
- Procédé selon la revendication 24, caractérisé en ce que l'éclairage de la surface du produit au travers du motif d'éclairage, pour l'examen de surface, a lieu dans une plage de longueur d'onde, dans laquelle la caméra utilisée pour l'examen de couleur n'est pas sensible.
- Procédé selon la revendication 24, caractérisé en ce que la plage de longueur d'onde de le motif d'éclairage se situe dans le proche infrarouge.
- Procédé selon l'une des revendications précédentes, caractérisé en ce que, pour l'identification de défauts de surface (50), les résultats obtenus lors de l'examen de couleur sont combinés avec les résultats obtenus lors de l'examen de surface.
- Agencement pour réaliser l'examen direct des inégalités (50) sur des surfaces selon le procédé selon l'une des revendications précédentes, caractérisé par un dispositif d'éclairage (43, 55, 61), qui est formé et disposé de telle sorte qu'il éclaire la surface du produit par un motif d'éclairage constitué par l'alternance d'éléments de luminosité ou de couleur différentes, par une caméra électronique (42, 60), disposée de telle sorte, qu'elle prend l'image du motif d'éclairage réfléchie sur la surface du produit, et par un dispositif d'exploitation (15) qui interprète les éléments d'image fournis par la caméra (42, 60) pour l'identification de modifications de luminosité ou de couleur dans l'image prise par la caméra (11) pour l'examen direct de la surface.
- Agencement selon la revendication 28, caractérisé en ce que le dispositif d'éclairage (43, 55, 61) présente une plaque ou feuille (44) transparente, sur laquelle se trouvent les éléments opaques (45, 46) du motif ainsi qu'au moins une source de lumière (48) qui éclaire la plaque ou la feuille (44) depuis la face arrière détournée de la caméra.
- Agencement selon la revendication 29, caractérisée en ce que les éléments opaques (45, 46) du motif sont des bandes parrallèles, qui forment avec les bandes de la plaque ou de la feuille (44) se trouvant entre elles le motif d'éclairage.
- Agencement selon la revendication 28, caractérisé en ce que le dispositif d'éclairage ( 43, 55, 61) présente plusieurs lampes écartées les unes des autres, qui forment avec les intervalles se trouvant entre elles le motif d'éclairage.
- Agencement selon l'une des revendications 28 à 31, caractérisé en ce que la caméra (42, 60) et le dispositif d'éclairage (48, 56, 62) sont disposés de telle sorte par rapport à la surface du produit (41) que l'image prise du motif d'éclairage est réfléchie à la surface du produit (41) sous un angle plat (α).
- Agencement selon l'une des revendications 28 à 31, caractérisé en ce que la caméra et le dispositif d'éclairage (48, 56, 62) sont disposés de telle sorte par rapport à la surface du produit (41) que l'image prise du motif d'éclairage est réfléchie à la surface du produit (41) sous un angle (α) de presque 90°.
Applications Claiming Priority (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
DE19638065A DE19638065A1 (de) | 1996-09-18 | 1996-09-18 | Automatische Qualitätskontrolle von Fliesen |
DE19638065 | 1996-09-18 | ||
PCT/EP1997/004973 WO1998012543A1 (fr) | 1996-09-18 | 1997-09-11 | Procede et dispositif pour controler automatiquement par voie optique la qualite de produits plats et lisses |
Publications (2)
Publication Number | Publication Date |
---|---|
EP0927348A1 EP0927348A1 (fr) | 1999-07-07 |
EP0927348B1 true EP0927348B1 (fr) | 2001-01-03 |
Family
ID=7806020
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP97909252A Expired - Lifetime EP0927348B1 (fr) | 1996-09-18 | 1997-09-11 | Procede et dispositif pour controler automatiquement par voie optique la qualite de produits plats et lisses |
Country Status (4)
Country | Link |
---|---|
EP (1) | EP0927348B1 (fr) |
DE (2) | DE19638065A1 (fr) |
ES (1) | ES2154032T3 (fr) |
WO (1) | WO1998012543A1 (fr) |
Families Citing this family (19)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP3315935B2 (ja) * | 1998-08-28 | 2002-08-19 | 吉野石膏株式会社 | 石膏ボードの製造方法及び装置 |
DE19916560A1 (de) * | 1999-04-13 | 2000-11-30 | Willing Gmbh Dr Ing | Lernfähiges Farbmeßsystem |
DE10002981B4 (de) * | 2000-01-24 | 2006-09-21 | Michael Giray | Verfahren und Vorrichtung zur Herstellung eines Formteils aus Sinterwerkstoff, pressbaren Keramikwerkstoffen o. dgl. |
EP1170576A1 (fr) * | 2000-07-07 | 2002-01-09 | Christian Stapfer | Spectres et cages chromatométriques, leur utilisation et la manière de les élaborer |
DE10118329A1 (de) * | 2001-04-12 | 2002-10-24 | Westfalia Landtechnik Gmbh | Verfahren zur Qualitätsprüfung bzw. zur optischen Charakterisierung von Milch und deren Vorrichtung |
DE20112088U1 (de) | 2001-07-18 | 2002-01-03 | ViALUX Messtechnik + Bildverarbeitung GmbH, 09126 Chemnitz | Vorrichtung zur Betonsteinprüfung |
DE10140660A1 (de) * | 2001-08-24 | 2003-03-13 | Visolution Gmbh Systemloesunge | Verfahren und Vorrichtung zur optoelektronischen Erfassung von Oberflächen |
WO2003031956A1 (fr) * | 2001-10-05 | 2003-04-17 | Millennium Venture Holdings Ltd | Systeme et procede de classification de pieces en fonction des variations tonales |
DE10258599A1 (de) * | 2002-12-14 | 2004-06-24 | Massen, Robert, Prof. Dr.-Ing. | Optische Erkennung von groben und feinen Objekten und Strukturen mit einfachen 1-Chip Farbkameras |
ITMO20060093A1 (it) * | 2006-03-21 | 2007-09-22 | System Spa | Metodo per l'individuazione di aree di disuniformita' su una superficie |
DE102010060375A1 (de) | 2010-11-05 | 2012-05-10 | Hseb Dresden Gmbh | Inspektionsverfahren |
PL2992295T3 (pl) | 2013-05-03 | 2017-07-31 | Csb-System Ag | Urządzenie i sposób klasyfikacji obiektu spożywczego o dojrzałej lub nieregularnej strukturze |
EP2919195B1 (fr) | 2014-03-10 | 2019-05-08 | Baumer Optronic GmbH | Système de capteurs pour la détermination d'une valeur de couleur |
CN107030870A (zh) * | 2017-04-05 | 2017-08-11 | 嘉兴职业技术学院 | 一种陶瓷器生产管理系统 |
EP3527972A1 (fr) * | 2018-02-19 | 2019-08-21 | Roche Diabetes Care GmbH | Procédé et dispositifs pour effectuer une mesure analytique |
TWI653417B (zh) * | 2018-08-14 | 2019-03-11 | 由田新技股份有限公司 | 光源模組 |
EP3767403B1 (fr) * | 2019-07-16 | 2022-09-07 | Carl Zeiss Industrielle Messtechnik GmbH | Mesure de forme et de surface assistée par apprentissage automatique destinée à la surveillance de production |
DE102022116099B3 (de) * | 2022-06-28 | 2023-12-28 | Carl Zeiss Industrielle Messtechnik Gmbh | Oberflächeninspektionssystem und Verfahren zur Erfassung von Oberflächendefekten |
CN116379934A (zh) * | 2023-05-08 | 2023-07-04 | 内蒙古大唐国际托克托发电有限责任公司 | 一种基于三维结构光测距的火电厂高温管道位移监测系统 |
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Publication number | Priority date | Publication date | Assignee | Title |
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JPS5939687B2 (ja) * | 1973-07-06 | 1984-09-26 | 工業技術院長 | 光のスペクトラム分布を用いた柄出しのための色分解法および装置 |
DE3639636C2 (de) * | 1986-11-20 | 1996-04-18 | Robert Prof Dr Ing Massen | Automatische Inspektion von Textilbahnen |
US4882498A (en) * | 1987-10-09 | 1989-11-21 | Pressco, Inc. | Pulsed-array video inspection lighting system |
US5221959A (en) * | 1990-03-16 | 1993-06-22 | Olympus Optical Co., Ltd. | Color discrimination data input apparatus |
DE4123916C2 (de) * | 1990-07-19 | 1998-04-09 | Reinhard Malz | Verfahren und Vorrichtung zum beleuchtungsdynamischen Erkennen und Klassifizieren von Oberflächenmerkmalen und -defekten eines Objektes |
DE4115067A1 (de) * | 1991-05-08 | 1992-11-12 | Chemnitz Textiltech Forsch | Verfahren zur automatischen farbmetrischen charakterisierung von mehrfarbig gemusterten flaechenbahnen |
DE4218971C2 (de) * | 1992-06-10 | 1994-09-22 | Grecon Greten Gmbh & Co Kg | Verfahren zur Kalibrierung eines Bildverarbeitungssystems |
US5335293A (en) * | 1992-06-16 | 1994-08-02 | Key Technology, Inc. | Product inspection method and apparatus |
DE4301018A1 (de) * | 1993-01-16 | 1994-07-21 | Steinbeis Transferzentrum Kons | Verfahren und Anordnung für die Verarbeitung von Farbzeilenkamera-Signalen |
US5495429A (en) * | 1993-02-12 | 1996-02-27 | West Virginia University | Method and apparatus for measuring the color of three dimensional objects |
DE4309802A1 (de) * | 1993-03-28 | 1994-09-29 | Robert Prof Dr Ing Massen | Produktionsnahe Farbkontrolle mit bildgebenden Sensoren |
AU6802694A (en) * | 1993-05-28 | 1994-12-20 | Axiom Bildverarbeitungssysteme Gmbh | An automatic inspection apparatus |
US5526285A (en) * | 1993-10-04 | 1996-06-11 | General Electric Company | Imaging color sensor |
DE4341894C1 (de) * | 1993-12-08 | 1995-07-06 | Betonwerk Lintel Gmbh & Co Kg | Verfahren zur Qualitätssicherung bzw. zur Qualitätsüberwachung von aus Beton hergestellten Produkten |
DE19503763C2 (de) * | 1995-02-04 | 1996-11-28 | Honeywell Ag | Vorrichtung zur Farbmessung |
DE19508052C2 (de) * | 1995-02-23 | 1998-08-06 | Nics Gmbh Ges Fuer Bildverarbe | Verfahren und Einrichtung zur Ebenflächigkeitsmessung von sich kontinuierlich bewegenden endlichen Materialoberflächen |
DE19511534C2 (de) * | 1995-03-29 | 1998-01-22 | Fraunhofer Ges Forschung | Verfahren und Vorrichtung zur Erfassung von 3D-Fehlstellen bei der automatischen Inspektion von Oberflächen mit Hilfe farbtüchtiger Bildauswertungssysteme |
-
1996
- 1996-09-18 DE DE19638065A patent/DE19638065A1/de not_active Withdrawn
-
1997
- 1997-09-11 EP EP97909252A patent/EP0927348B1/fr not_active Expired - Lifetime
- 1997-09-11 DE DE59702864T patent/DE59702864D1/de not_active Expired - Lifetime
- 1997-09-11 WO PCT/EP1997/004973 patent/WO1998012543A1/fr active IP Right Grant
- 1997-09-11 ES ES97909252T patent/ES2154032T3/es not_active Expired - Lifetime
Also Published As
Publication number | Publication date |
---|---|
DE19638065A1 (de) | 1998-03-19 |
EP0927348A1 (fr) | 1999-07-07 |
DE59702864D1 (de) | 2001-02-08 |
ES2154032T3 (es) | 2001-03-16 |
WO1998012543A1 (fr) | 1998-03-26 |
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